{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7caa0c5f",
   "metadata": {},
   "source": [
    "测试执行HelloWorld代码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0e0095d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello World!\n"
     ]
    }
   ],
   "source": [
    "print(\"Hello World!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec041946",
   "metadata": {},
   "source": [
    "测试图表功能"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c05d2dea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bTyCPEUYBAIgVc+ZIV18ttWghffKJNHx48H3rltS9OyEUIUUYBQAg2n39tdSmjdS6tfTVV8HhNCXFy5EBhFEAAKLS6dPSl19KrVq5QdQCqU/NmtK//y2tXCkVKuTlKAFO0wMAEHUSE6X/+z93b2igWrWkp5+Wbr9dKkgEQHjgf4kAAESb8uWlrVv97y++WHrmGem226QCBbwcGRB+y/QpKSm65JJLvB4GAACRuxy/alXwNTuAZPVBa9eW3nlHWrNGuuMOgijCkudhdOLEifr111+9HgYAAJEXQmfNkpo1kxo0cGuCBrrnHmn1ane5nhCKMOZpGN28ebNKlSqlEiVKeDkMAAAiK4TOnCn9/vdu/3jrI3/qlDRkSPBztieUEIoI4GkYff/999W1a9ezPnfs2DElJycHvQAAiLkQ+vHHUpMm0vXXS4sW+e/VqyfdcIOXowMiL4xOnz5dnTp1ytKzw4YNU3x8fOqrSpUqeT4+AADCJoROny41buwGziVL/Pcuu8xmdtwSTbfc4uUogcgKozazaftEL7bTfVnw1FNP6cCBA6mvRCtZAQBALPjvfyWbvFm61H+tfn3pgw+k5cvdEJrf8yMgQGSVdpo/f74KFy6s9957z3n/22+/OZ83bNgww4AaFxfnvAAAiDkdO7pF6jdudA8qDRjghlMCKKJEvtOnbf4/92zdulVVq1bN1tdUq1ZNW7ZsydbMqi3X2yxpyZIlczBKAADCjB1C+vBDdxl+6NDgezNmSCdPusv0+fJ5NUIgW7Ka13J9ZnTBggXZDqOWh+2Vj/+DAQBiMYTakvvf/+6vF2odki691P+MHVgColSWw+igQYOcWc8zsUC5YsUK/Z/VNMuCHTt2aNq0ac4e0P79+6tXr16qVKlSVocEAEBkh1A7fDR4sFsPNNC779rpXa9GBoTnMr2FzJkzZ+oO6+BwBm+99Zaetr63eYhlegBAxLLldguhNhO6dm3wvaZN3T2h7dqxHI+Il+vL9A0aNNCuXbvOugR/mZWZAAAA6X36qdS3r/TDD8HXrYD9wIHSddcRQhFzsrVn9Nprrz3rM1mtHQoAQMw5eDA4iF55pTsTan+/EkIRozwp7QQAQNQ7cULat08qV85/7eab3W5J8fHuTOg11xBCEfNyvUiZLeUDABDTIfTNN6W6daVu3YLvWW3Qr7+W5s2T2rYliAJ5EUZnz56d298SAIDICKFvvCHVqSPdfbe0YYM0c6a0eHHwc2XKEEKBnC7TN2rUSAMGDHD2hXbv3j1dXVA7mL9y5cosl3YCACDipaRYKRlpyBBp06bge61bSwXZEQecSbb+H/Liiy+qnu11kfS73/1Od911V7pn/v3vf2fnWwIAELkh1JbjLYRu3hx87+qr3YNJLVt6NTogOsPolXbq739atmyZYZmn5s2b587IAAAIZ7YKaPVCA9k+UAuh/F0I5P2e0VatWmV4/Wr71yAAANGuRw//51aaaf58OzhBEAWy6Zw2svzyyy86YRu2A8yfP589owCA6HHsmDRxonV1ceuC+liXpIcflrp2lZo183KEQGyG0Ztuuslp8ZTfylQEWLNmDWEUABAdIfT116Xhw6XERPcw0ldf+e/bId5Ro7wcIRDbYbRFixZ65JFH0l3fnHYTNwAAkeToUTeEDhsmbd/uv271Qb//3p0hBeB9GLXi9h07dlRCQkJQaSebGV20aFFujQ8AgNCF0Ndec2dCf/kl+N7110v9+xNEgXAKo4cOHXJKPaVdpp87d25ujAsAgNA4dUoaO9YNoTt2BN+74QY3hF5xhVejA6Jejk/TV65cWUlJSU7h+7QvAAAihk2qTJsWHERvvFFaulT66COCKBCuM6Pvvvuu1q9f7yzNB7Jl+j/96U+5MTYAAHLf4cNS0aLBLTmtNqjtCe3c2Z0JbdDAyxECMSXHYfSbb75R8eLF011PTk4+1zEBAJD7fvtNeuUV6fnn3VJNHTr479lJ+XXrpFq1vBwhEJOytEz//vvv64UXXtDWrVtTr2UURE3JkiVzb3QAAJyrQ4ekESOk6tWlxx6TkpKkQYPs1G3wcwRRIHxnRm+99ValpKRoypQpzvK8tfy00k4AAIR1CH3pJWnkSGn3bv91W56vVs2dKc1kYgVA6OQ7nXbTZxZYl6U5c+aoWrVq6tq1qwoVKqRQsq0AVnD/wIEDzMQCAIIdPOiejn/hBWnPnuAQ+sc/Ss88I9Wt6+UIgZiQnMW8lqMw6rNt2zZNnjzZCaO33Xabypcvr1AgjAIAMmQzoLVrpw+ht98uPf20VKeOl6MDYkpyKMKoz+HDhzVp0iTt3LlT7dq10+WXX668RBgFAGTKCtTPnOmWbPKFUAuoAKI3jAb65JNPtGLFCj3++OPpCuLnFsIoAEAHDkhvvindf78bPH2sC+CLL7oh9OKLvRwhENOSvQqjoUAYBYAYtn+/9M9/SqNHu59PmWInbb0eFYAc5rW8mboEACC37dvnFqe3k/ADB7pB1Awdmr5ME4DoLXp/5MgRPfDAA7rqqqsyvG/tQKtUqaK2bdvmxvgAALFu715p1ChpzBibavFfL1BAuvtuqV+/4G5KACJKtmdGT506pblz56pAgQIaOXJk6seCBQs6nxs7Wb9y5cq8GC8AIJZCqO37tJnQZ5/1B9GCBaWePaX166XXX5dq1PB6pABCNTM6bdo0de7c2Zn5vPvuu/XGG2+kfrzrrrtSn9u4caPq169/LuMCAMS67dulIUP87y2Edu8uPfWU200JQGzNjM6cOdOZ8fzoo4+CluQDP/rcc889uTlGAEAsOHUq+P2ll0q33CJZY5X77rOZDmn8eIIoEKszox06dNCVV17pFLj/9ddf1b9/f23evDnoozl58qRq1Kih6vywAABkxa5dbsvOzz6TFi92Z0B9nn9e+sc/pAsv9HKEAMJlz6jNgLZv315lypTRNddco1KlSqV+vPrqq9WmTRu1atVKCQkJeTdiAEB0SEqSHnvM3RM6YoS0YoX07rvBz9jEBkEUiGpZmhldsmSJM/vpY7OjFjpLly7tfLQw2rp167wcJwAgWuzc6c54vvKKtfDzXy9cWPrlFy9HBiBcw+jRo0c1ceJErV69Wj/88EO6+2n3jAIAkM6vv7ozoK++anUC/dfj4qQ//1l64gmpUiUvRwjAA9nqwDR79mw9/fTTzp7RatWqyfelVlm/UqVKatGihfr06aNixYrl5ZjpwAQAkea999yT8EeP+q8VKeIeTHr8caliRS9HB8DDvJat0k7XXnutGjdurF69ejkHlurWrZt6z4LpnDlznHvDhg1zwikAAI4rrpBSUtzPixaVevVy94tWqOD1yABEWtF72x/6zjvvaMaMGemW6m3f6IQJEzRp0qTcHCMAINLqg86bF3ytZk13Kf6vf5U2bXJPyBNEAWR3mT7QsWPHFGf7fDJw/PhxZ2q2bNmyygss0wNAGPr5Z2n4cOm116Ty5aUNG9z9oABiUnIW81q2Z0Z9MguipnDhwnkWRAEAYWbbNukvf3Hbcr70ks1ISImJ0htveD0yABEgW2H0yJEjzjK8jyXdoUOHpnumW7duuTdCAEB42rrV3ftpS/BWpslCqDnvPPdk/M03ez1CANEWRocPH663337b+dzagr733nv6/PPPnfffffed8zEpKclpHQoAiFJbtrj7Py+6SBo3zn8wqXhxt2+83bfl+nLlvB4pgGgKo4cPH9bAgQOdU/Mff/yxRo8erfvuu895b0G0X79+znNVq1bVJZdckpdjBgB4yQrW275QXwgtUUKyvwMshNpqGdu0AOR2GJ0+fbruuOMOnTp1yjk137Fjx9R79r5p06bOvcBrAIAo9eST1opPsgMJTz/thtAhQ6QyZbweGYAIlKU6ozfccINT0umFF17I9Jn9+/dr7ty5zkypfQ4AiHA//eSGzAYNpIce8l+vUkWaOlVq3lwqXdrLEQKIAlkuem/dlez1ySefZHh/3759zv5RC6P2OQAgQm3cKD37rGRnBE6elBISpHvukQK7691wg5cjBBBFstWBySxZskQ9e/Z0Dirt3r079Xr16tX197//3fl8/vz5uTtKAEDeW7/eDaHvvCMFbL1yTsl//730+997OToAsX6A6eeff9a6devUqFEjPfroo0pJSVHv3r2daytWrHCK4PuwZxQAIsi6ddKdd0p16khvveUPorYEP3iwuyeUIArAyzBqtUO7dOmirVu3OkGzTp06Tu/5KVOmqEqVKk77z2bNmuXVGAEAecVKNNWt6y7J+0Lo+ee7M6QWQu2AUny816MEEOth1ELof//7X1133XWp13xdRIsWLarnnntOv//97/Wf//wn9d7OnTvzaswAgNxiJ+J9IdROw1tpJguhf/ubew8AwiGM1q5dWwm2gf1/feeNhc/AJXmbOS1WrJizZP/iiy+qvPUlBgCEj9WrrXVe8LXHHpMuvNAtUr95s1u03uqGAkCIZLs3va+4/bBhw5yPgfVFrQTUTz/9RNF7AAgnq1ZJXbtKl14qjRkTfM8mDjZtctt3EkIBeCDfad96ew4dOnRIxa0F3P+cOHHCqTNaNg87cCQnJys+Pl4HDhxQSZaRACBjdgLeqpxYTVAfO5Rky/D87ASQx7Ka17I9Mxpo8eLFzil6K/XkU7BgQT3zzDNO+1AAgAdWrpRuuUWqXz84iNosqB1Isu5JABBJdUZtttMCpu0dtWV52zdarlw5jR07VlOnTtXSpUtTn12wYIHzOscJVwBAdi1f7s6Efvhh8PULLpAef1y6777gwvUAEAayNDN68uRJzZgxQyVKlHCmWS2E/uEPf3ACZ+nSpZ2XWbZsmXOy3ro0nXfeeXk9dgCAj61GtWkTHEQrVJBGj3b3hPbtSxAFELlhNC4uTmXKlNHNN9+sW265xZkVtbDpO0lvS/XvvfeeVq9erWnTpqlixYp5PW4AQCALmr7+8fYz+J//dHvL9+ljNfi8Hh0AnPue0Yy6KtlMaMuWLfXjjz/q+++/d3rXFyhQIKvfEgCQE4sXS7feKgW0ZHY8/LA0dqwbQi2YEkIBRIBzOsDUsGFDzZ07V/Xr13dmTQcNGqQJEybk3ugAAH7ffSd16CA1aeIeTHrhheD71jnp/vulIkW8GiEA5E0YtQNL1oXp+uuvd162HG896X0F8G3W9IorrtAbb7zhXJs+fXr2RwIAyNjChVL79m5/+Fmz/Nc/+sg29Xs5MgAIzWn6woULO8Xs07r22mudj3v37nWW6S+77DL16tVLo0aNckKpfR0AIIe++UYaNEj67LPg69YxyRqQdOsmsTUKQKwXvTc2I9q2bVuNGTNGAwYMcGqNWlvQpk2bnvHrvvrqK61Zs0YpKSnOTOvw4cNVqlSps/56FL0HENW2bpXuvVeaPTv4etWqbs/4u++2WQKvRgcAWZLVvJblMPrzzz87s55PPvmkmjdvrqFDhzqzn/nz+1f6165dqyVLljgn6i+1tnNnUa9ePa1atcpZ5rel/dmzZzuBNrd+cwAQkQ4dkqpVk/bscd/b5xZC77qLEAogYmQ1r2Vpmd5Y6ab+/furiW2cl3TxxRermv2ADGD7SRMTE7Pcm/7GG290apjaTGqtWrX02muvZXU4ABD5bC5g/Xpp/nypRw/bgO9etxbLjz4qjR/vdky68066JgGIWjlepp80aZJuuukmFc2l0iHPPvusE2I7d+6c7p7VMbVXYNKuUqUKM6MAIov9uP3xR+nrr6U5c9yPO3e699askerW9T979Ki7H5QQCiBC5frMaFqdOnXKlSC6efNmPf30085e0X62IT8Dw4YNc8pGAUDEhc8ffnBDpy+AJiVl/KzdDwyjlGcCECNy5QBTbnjzzTedE/kjR45Md4+ZUQAR6dQpqVw5KzmS8X1bjm/RQmrVSrrpJtv/FOoRAkDkHGAKhbJlyzp7Ts8248oBJgBhEzZXr/Yvuduy+uTJwc/Y1iNfv3j7eeULn61bW+cQqWCOF6gAILaX6c/V4cOH1bVrV3300UdBJ/LthH5u7UMFgFwPn99/7w+fc+cGz3ra0rqt4sTF+a/ZwaTmzd3w2aABdUEBIJzC6KJFi1KDqNUZtVJPlqABIKzYoaMnnpDmzZP27cv8OQuj1iAkcO/nDTeEZIgAEKkKerkk/8orr+i5555TiRIltH79er3zzjteDQcA3NaaK1a4y+kXXRS8t9Nab6ZVurR/yd0+Wn1lZj4BIFs83ax0yy23ePnLA4h1J05Iy5f7l91t5jM5WerTRxo92v9c5cpSzZrurKiFTl8ArVdPCthmBADIPnbOA4it8Llsmb/MkoXPgwfTP2f307L9oeXLEz4BIJcRRgHEjgEDpKFDM79vZZhs1rNNG7dGqK8jkqlQISRDBIBYQxgFED2OH5eWLPEvu7/8slSjhv++lVUKZDOdgXs+69QJDqAAgDxHGAUQ2eFz8WL/svuCBVaqw3/frgeG0auukm67zR9Arcg84RMAPEUYBRB5Ro2SZsyQvvlGOnIk8+eWLpV69vS/L1FCmjQpJEMEAGQNYRRA+LIC8uvXuyWTAn3+ufTFF+mft1PvviV3+xg4KwoACEuEUQDh4+hRaeFC/55P+9zaZVpJpcC2mRY2Z86UqlRxQ6fvVb06y+4AEGEIowC8Y0vs337rD5/ffefOhqZl5ZiaNPG/79ZN6tJFqlaN8AkAEY4wCsAbO3a4YdIOIWXG7tuMZ9GiwdcTEvJ8eACA0CCMAsg7v/3mHjKyWU9bUu/Vy3/vggvc0kqJif5rv/udf8+nvapW9WTYAIDQIYwCyD2HDrnllXyllqzsknU9Mo0bB4dRW16/4w5p1y5/ALXACgCIKYRRAOdm7VrpzTfdAGoF50+ezPg52/dpYbV4cf+1YcNCNkwAQHgijALIuuRkqUAB6bzz/Nc2bJCeey7j52vXDu5wFBhEAQAgjAI4owMHpPnz3VlPe9ns5htvSHfeGdxi05bcrZe7tdP0lVlq2dLdFwoAwBkQRgH47d8vzZvn3/O5fLl06lTwM3YvMIyef75b87NhQ/dAEgAA2UAYBeDq3VsaN86d4cxMvXruife02rXL06EBAKIXYRSIJXv2SHPnuuWWhg9393/6VKqUPohedpl/z6ctu5ctG/IhAwCiG2EUiGZWNsnCp6/D0apV/ntWVqlBA//7Nm2k+vX9ez5tL2iZMp4MGwAQOwijQDSxskrTpvn3fK5enfmzdj8wjF51lbRiRUiGCQCAD2EUiGTWxz0uzv8+f37pgQeknTvTP2v37JCRr8ySzXwCAOAxwigQSX791b/kbh9tGd1Ov/tYiSULmpMnu+GzUSP/ns/mzaX4eC9HDwBAOoRRIJz98osbOn0BdN264PuFCkmHD0vFivmvPfywdPfdbvgsWTLkQwYAIDsIo0A4WrpUuv12t7tRZuwkvM182mxpYLmlZs1CMkQAAHIDYRTwUmKiO+tZq5bUpIn/epUq6YNowYJS48b+0+5XXkl7TQBAxCOMAqG0dWvwns9Nm/wF5wPDaEKCe9LdesD7DhxZ+AzsCQ8AQBQgjAJ56eefpc8/94fPLVsyfs7up7VkSXBRegAAohBhFMgtvu5FdqLdZ/x4afDgjJ8vXNjd3+k77Z4WQRQAEAMIo8C5hE9bZvfNetrHTz+V6tTxP2NB0xdGrR6ohU/fsnvTplLRop4NHwCAcEAYBbITPjduDN7zacvwgex6YBi18DlokBtAbU9okSIhHzYAAOGMMApkhXU1sjabVvczMzbLuXt38DWr/9m/f54PDwCASEUYBQJnPq2o/Pr1UqdOwfe2b08fRC1oWj9337K7lV2yfaAAACDLCKOI7fD5ww/By+7W091mOPftC+75bmFz9my3q5HvwJEVnCd8AgBwTvKdPu07Ahw5kpOTFR8frwMHDqgk7Q6RVfY/9bVr/cHTXklJGT9r/d4tePpYy01rvWkvAACQa3mNmVHEDltqr1cv8/slSkgtWriznlWrBt8L7P0OAAByDWEU0ePUKWnVKv+y+2WXSQMH+u9Xruz2cPd1PbJ/pbVs6V92t45H1nITAACEDH/zIrLD5/ffu8HTXra0vnev//7mzcFh1PTtKx0/7gZQC58UlgcAwFOEUUQeC50jR0pz50r792f+XGKiu9czcIndSjQBAICwQRhF+DpxQlqxQqpWTSpb1n/90CHpo4/SP3/++e6Mp2/Z/dJLpfz5QzpkAACQPYRRhFf4XL7cv+w+f74dxZP+9S+pZ0//c1bb05bXS5d293xa8LTXJZcQPgEAiDCEUXgnJUVatsx/4MjC58GD6Z+z+4Fh1A4e/fijexiJ8AkAQEQjjMI7XbtKH36Y+f2EBHfGs1279Pdq1szToQEAgNAgjCLv2Kn1JUvcWc+FC6UPPggundSsWXAYveAC/35Pe118sZQvnydDBwAAoUEYRe45dkxavNjf4WjBAunIEf99W5Jv0sT//rrr3ANKvgBaqxbhEwCAGEMYxbnv+xw+3A2g334bHD7TstnRwDBqdT7ffTckwwQAAOGJMIqsO3pU2rFDql7df82W3V97za3pmZZ1PPItudvsZ40aIR0uAAAIf4RRZM5mOW0207fsbp/Xry99953/GVtWt6D59tvShRcGh08LrSy7AwCAM8h3+vTp04owycnJio+P14EDB1TSyvwgd1i3Il/4tJeFTjuEFMjqe+7bJ5Uo4b+2YYNUqJBbnB4AAEBZz2vMjMJlrTXbtnX3gGbGZjpt1tNqgQaG0YsuCskQAQBA9CGMxhJro/nNN+6Su3Uu+sMf/Pfq1XM7IAWyPZ6+JXd72TI8AABALiKMRjObwbTySr4OR1bz0xc4d+4MDqPW1/3GG90e8L4AageQAAAA8hBhNNosWiRNneqGz6VLpZMnM37O7qc1bVqeDw8AACAQYTSSHTjg7t0M7M/+2WfSiBEZP1+njr/AvC3TAwAAeIwwGkn275fmzfMvuy9f7nY1snJLPhY0ferWDd7zWb68J8MGAADIDGE0nFkJJQufvjqfFj7TVuKye4FhtHFjafJkN3wmJIR8yAAAANlBGA1X7dq5S+5nKgN76aVS8eLB1+LipC5d8nx4AAAAuYEw6qXdu936ntu2SQ8/HHzPisOmDaI2A+rb89mihXvyHQAAIIIRRkNp1y43fPo6HK1e7V4vXFj685+lYsX8z159tdvZyNde08KnlV8CAACIIrQDzUu//SbNnOnf87lmTebPfvGFG0B97I+Fvu4AACBC0Q7UC1bT03q3B3Y86to142etHNPll/uX3e3gUSCCKAAAiAGehtEVK1boyy+/VKFChbRq1Sr17t1bDRs2VMTYscOd8fSVWrKZzZde8t+3UkpW2/OHH9yQ2qiRP3xedZUUH+/l6AEAAGI7jD711FOaNWuW83lSUpI6deqkhQsXKmxt3x4cPtevD74fWHzeZ+hQqUgRN3xagXoAAAB4H0Z37dqlOXPm6PDhwypWrJgSEhK0206Xh6P//ld67DH3QFFmChZ0ZzqPHXPLK/ncdFNIhggAABCJPAuj5cqVc2ZFLYiavXv3OtcycuzYMecVuCE2pKyWZ9ogauGzSRN/h6Mrr0xf8xMAAADhu0zfykLc/4waNUqDBg3K8Llhw4Zlei8kmjVzg2aDBv7wadfOO8+7MQEAAESBsCjtNHv2bG3fvl3dunXL8sxolSpVQlva6fhxtx4oAAAAoqe009KlS5WYmKgePXpk+kxcXJzz8hRBFAAAINdlcPw7dLZu3aqvv/46NYhu3rzZOdAEAACA2OBZGE1JSdH48ePVt2/f1Gvjxo1TESuDBAAAgJjgWRj97LPP9Oqrr+rCCy9U5cqVndJO77//vvJnVKsTAAAAUcmzPaPXX3+99uzZ49UvDwAAgDDANCQAAAA8QxgFAACAZzwv7ZQTvtKoIe/EBAAAgCzx5bSzlbSPyDB68OBB56MVvgcAAEB45zYrfh/WHZiy69SpU/rll19UokQJ5cuXL89/PV/HJyvOH7KOTwBiCj9nAETbzxiLmBZEK1aseMZqSRE5M2q/ISsHFWr2h8dfEgDyEj9nAETTz5gzzYj6cIAJAAAAniGMAgAAwDOE0SyIi4vTgAEDnI8AkBf4OQMgVn/GROQBJgAAAEQHZkYBAADgGcIoAAAAPEMYBQAAgGcIowAAAPAMYRQAAACeicgOTKG0adMmffHFFxoyZIi2bNni9XAARKEVK1boyy+/VKFChbRq1Sr17t1bDRs29HpYAKLIV199pTVr1iglJUXr1q3T8OHDVapUKYUDSjtl0YUXXqht27Z5PQwAUah9+/aaNWuW83lSUpI6deqkhQsXej0sAFGkXr16zj928+XLp+nTp2v27NkaM2aMwgHL9FmUPz//qQDkvl27dmnOnDk6fPiw8z4hIUG7d+/2elgAosyNN96okydPOp/XqlUrrFZ7WaYHAA+VK1fOmRUtVqyY837v3r3ONQDITbbd0GfKlCnq3r27wgXTfQDgsVatWqV+PmrUKA0aNMjT8QCITps3b9Ydd9yhHTt2ODOl4YIwCgBhwvZw1ahRQ9ddd53XQwEQhapXr6533nlHTZs21eOPP65wwQGmLKpWrVpY7a8AEF2WLl2qlStXqkePHl4PBUAMKFu2rBITE1W0aFGvh8LMKAB4bevWrfr6669Tg6gtpfkONAHAubKfJx07dtSpU6eCrh8/flzhgDCaRfYHyCQygNxmNf/Gjx+vvn37pl4bN26cihQp4um4AERXGF20aFFqZSCrM2qlnuLj4xUOWKY/i59++klTp07VU089pT59+jgbfxs1auT1sABEiRkzZuiuu+5KXSqzmYqSJUtq48aNXg8NQBSZOnWq83OlRIkSWr9+vR577DFVqlRJ4YAwCgAAAM+wTA8AAADPEEYBAADgGcIoAAAAPEMYBQAAgGcIowAAAPAMYRQA8ojV9Zs0aVK66wcPHjzn7z19+nQdO3bsnL8PAHiNMAoAOXT06NHUz/fs2ZPuvl379ttv0123Wn8PPvhgum4ogawj05lY69C4uLhsjxkAwk1BrwcAAJGqffv2qZ3ZVq1apU8++USNGzdOvV+gQAGdf/75QV+zf/9+NWzYUPv27XNmTidMmKDvv/8+XcelFStW6NNPP1XTpk3T/bpz585Vy5Yt8+z3BQChRBgFgHOYGfXNfLZu3VqXX3550P18+fI5H5ctW+Z0VapZs6ZeeukllStXTs8++6wqVKjgtAL1OXHihAoWLJj6/TIKombevHn629/+loe/MwAIHcIoAOSQr8+zz8CBA/XZZ5+ltva02c8DBw44S+4NGjTQ6NGjnbCZkJCgatWqaejQoU470EKFCjnPW4u+pUuXOiE1M1u2bFHVqlXz+HcGAKFDGAWAXDJ48GDdf//9uuCCC5z3n3/+uebPn++E1LSzpcaW+AcNGqS2bds679u1a3fGIGqmTJmihx56KN1MqQVZO9A0atQojRgxQp07d87l3x0A5A3CKADkkAVLW0737fE048aNc/ZztmnTJtOv8fEtyWf2Pq3ffvvNmUVNe3DprbfeSl3u79Chg2bPnp3D3xEAhB5hFAByyGY2fafefaG0d+/eqlevnrOcnpVl/kceeUSlS5d23icnJ5/x+XfffVe33XZbuuuHDh3SxIkT1bVrV2f5v2fPnjn8HQFA6FHaCQByke0HtdnJzGY5A2dGT548qRdeeMEJtPayrz1T8E1KSkrdAhDIZkV37NjhnOQP3BIAAJGAMAoAOeQr65T2vc1SFi5c+KxfY2HUZkZtVtVeiYmJmf5as2bNcvaUppWSkuKc6u/Xr5+zVcC+58iRI8/hdwUAoUUYBYAcsuDnC5IWBC0Ypp39PBMr9/T222+nzozaMntm7JR9o0aN0l23X9NO6RsLwI8++qh2796d498TAIQae0YB4Bz49owOGTIkXQjNqMOSXfNdty5MgQYMGOAUxS9VqpQTdH3Wrl2runXrZvjrFytWTGPHjtXhw4ed8lHW9SntaXsACGeEUQDIoQ8//DD188Ai9Bs2bNDkyZP1wQcfqHv37kFfYyHzyJEjmX7PxYsXO7Obvtqj5uOPP3aW8zNjARYAIlW+02k3PQEAzpn9aH355Zedk+2BrT7toJF1YDpTGadt27Y5bUSLFy+erjMTAEQbwigAAAA8wwEmAAAAeIYwCgAAAM8QRgEAAOAZwigAAAA8QxgFAACAZwijAAAA8AxhFAAAAJ4hjAIAAMAzhFEAAADIK/8PP1zaWxVUizgAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import MaxNLocator\n",
    "\n",
    "# 设置中文字体和解决负号显示问题\n",
    "plt.rcParams['font.family'] = 'SimSun'        # 字体设置为宋体\n",
    "plt.rcParams['font.size'] = 10               # 字号设置为小五（10pt）\n",
    "plt.rcParams['axes.unicode_minus'] = False    # 解决负号 '-' 显示为方块的问题\n",
    "\n",
    "plt.figure(figsize=(8, 3))\n",
    "plt.plot([1, 2, 3], [2, 3, 5],linewidth=2, color='red', linestyle='--',label='Custom item')\n",
    "plt.xlabel(\"时间/s\")\n",
    "plt.ylabel(\"误差角/mil\")\n",
    "plt.legend()\n",
    "\n",
    "# 设置 x 轴和 y 轴刻度为整数\n",
    "ax = plt.gca()  # 获取当前坐标轴对象\n",
    "ax.xaxis.set_major_locator(MaxNLocator(integer=True))  # x 轴仅显示整数\n",
    "ax.yaxis.set_major_locator(MaxNLocator(integer=True))  # y 轴仅显示整数\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1836089",
   "metadata": {},
   "source": [
    "字符串操作"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9abf450e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello Ada S'Tone\n",
      "I love Da Wei.\n"
     ]
    }
   ],
   "source": [
    "# 字符串建议使用双引号，单引号可能会和字符串内部的单引号冲突\n",
    "first_name = \"Ada\"\n",
    "last_name = \"s'tone\"\n",
    "# f代表format\n",
    "full_name = f\"{first_name} {last_name}\"\n",
    "# 字符串的title()函数指的是首字母大写\n",
    "print(f\"Hello {full_name.title()}\")\n",
    "\n",
    "# rstrip()去除字符串两端空白\n",
    "love_girl = \" Da Wei \"\n",
    "print(f\"I love {love_girl.strip()}.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3392b45",
   "metadata": {},
   "source": [
    "Python数字操作"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f4cb33f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8\n",
      "2.0\n",
      "<class 'int'>\n",
      "<class 'float'>\n"
     ]
    }
   ],
   "source": [
    "# 幂操作\n",
    "print(2 ** 3)\n",
    "\n",
    "# 浮点数\n",
    "print(4/2)\n",
    "\n",
    "print(type(4))\n",
    "print(type(4/2))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "py313_learning",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
